Intracranial pressure (ICP) and compliance are important clinical parameters for diagnosis and treatment of diseases of the central nervous system (CNS). Elevated intracranial pressure, if left untreated, may result in patient death or permanent damage. Techniques currently available to measure ICP are invasive and associated with risk. In addition, penetration into the CNS space to measure the ICP often alters the pressure.
In a closed system, such as the cranium, the inside pressure and volume are related. The change in pressure due to change in volume is determined by the overall mechanical elastance of the system. Studies of the relation between intracranial volume and pressure date back almost 200 years. In 1873, Alexander Monro stated that the intracranial space contains two compartments (brain matter and blood) that can change in volume. Since neither can be compressed and the cranium is rigid, he concluded that the volume of blood within the intracranial space is constant. Sixty years later, in light of the discovery of the CSF by Magendi, Burrows concluded that intracranial blood volume does change and it is accompanied by a reciprocal change in the volume of the other two compartments, brain and CSF. This is known as the Monro-Kelli doctrine. The majority of the added volume during systole is accommodated by displacement of the CSF into the spinal canal.
Ryder and others injected fluid into the CNS space to find the relation between the intracranial pressure and volume. The derived pressure-volume curve, also called the elastance curve, is well described by a monoexponential curve. The elastance (inverse of compliance) is defined as the change in pressure due to a change in volume (dP/dV). The intracranial elastance (i.e., the derivative of the pressure-volume curve) is therefore also an exponential function of the intracranial volume.
The most practical method of assessing the volume-pressure relationship is the volume pressure test. In this test, the total volume of the system is rapidly loaded by injection of a uniform amount of fluid into the lateral vertical. The pressure change resulting from the volume loading is termed volume-pressure response (VPR).
In both clinical patients and experimental animals, the relationship between VPR and ICP has been shown to be linear. This linear relation validates the monoexponential volume-pressure relation. The elastance coefficient (the coefficient defining the shape of the volume-pressure exponential curve) is determined from the slope of the VPR-ICP linear relationship. The intracranial compliance coefficient is the reciprocal of the elastance coefficient.
In clinical practice, intracranial pressure is often measured for the diagnosis and clinical management of closed-head injuries such as trauma and intracranial bleeding or of chronic disorders such as hydrocephalus, malformations involving hindbrain herniation and pseudotumor cerebri. Intracranial pressure measurement is an invasive procedure and thus it is associated with risk.
Our non-invasive method for measurement of the intracranial pressure, described below under illustrated embodiments of the invention, utilizes measurements of the pulsatile blood and CSF volumetric flow rates (see FIGS. 2 and 3, items 40, 42, 44, 46, 48 and FIG. 5). In general, the lumen of the flow conduit has to be delineated in order to calculate the flow rate. A number of past efforts have been reported which have been directed to this problem. These efforts have been only partially successful.
For example, Burdart et. al. developed an automated segmentation technique for phase contrast MRI images using pixel intensity differences between vessel and background within a single image. Using the fact that pixels have either positive or negative intensity magnitudes depending on their direction (whereas stationary pixels have intensity value significantly closer to zero) the vessels were threshold against a pre-selected threshold index. Hu et. al. used a region growing technique with an intensity threshold to segment the entire vascular structure in a set of three-dimensional MRI images of blood vessels. Singleton and Pohost extended the region growing technique to segment cardiac lumens using a region growing method, along with eroding and dilating operations, to include holes and excluding isolated regions outside the ventricle. Baledent et. al. segmented CSF flow area in phase contrast MRI technique using the fundamental frequency component, obtained from Fast Fourier Transform to enhance the pulsatile dynamics.
Cross-correlation technique has also been used, as an image processing technique for applications not related to segmentation of flow regions. Bandettini et. al. used cross-correlation between a reference pattern and image intensity values in echo-planar MR images that were acquired during brain stimulation. Regions in which signal intensity changes correlated with the activation pattern were identified as the active region in the brain. A arbitrary threshold value was used to differentiate between activated and background regions.
The ability to automate the identification of the lumen's borders for quantification of volumetric flow measurements would make the results more reproducible and reliable and less dependent on the skills of the operator. With automated blood and CSF flow measurements, ICP measurements will become more reliable. Therefore there is a need to automate identification of the lumen borders for quantification of pulsatile CSF and blood flow rates.